A Bioinformatics Approach to Prioritize Single Nucleotide Polymorphisms in TLRs Signaling Pathway Genes

It has been suggested that single nucleotide polymorphisms (SNPs) in genes involved in Toll-like receptors (TLRs) pathway may exhibit broad effects on function of this network and might contribute to a range of human diseases. However, the extent to which these variations affect TLR signaling is not well understood. In this study, we adopted a bioinformatics approach to predict the consequences of SNPs in TLRs network. The consequences of non-synonymous coding SNPs (nsSNPs) were predicted by SIFT, PolyPhen, PANTHER, SNPs&GO, I-Mutant, ConSurf and NetSurf tools. Structural visualization of wild type and mutant protein was performed using the project HOPE and Swiss PDB viewer. The influence of 5′-UTR and 3′- UTR SNPs were analyzed by appropriate computational approaches. Nineteen nsSNPs in TLRs pathway genes were found to have deleterious consequences as predicted by the combination of different algorithms. Moreover, our results suggested that SNPs located at UTRs of TLRs pathway genes may potentially influence binding of transcription factors or microRNAs. By applying a pathway-based bioinformatics analysis of genetic variations, we provided a prioritized list of potentially deleterious variants. These findings may facilitate the selection of proper variants for future functional and/or association studies.

Accumulating evidence now suggests that genetic variations in TLRs pathway genes may exhibit deleterious effects on gene function, leading to the dysregulation of this signaling pathways (7)(8). Single nucleotide polymorphisms (SNPs) are the shortest and the most frequent variations in the human genome. Among these, the functional consequences of untranslated regions (UTRs) and non-synonymous (nsSNPs) SNPs are of special interest, as they can either modulate gene expression or influence protein structure and function (9)(10). Although the contribution of SNPs in TLR signaling to human pathological states was addressed by several studies, a comprehensive and prioritized list of SNPs potentially affecting the function and regulation of this pathway is still lacking. Therefore, this study aimed to systematically identify the UTR-SNPs and nsSNPs in genes involved in TLRs signaling network by employing a bioinformatics approach and predicting their deleterious functional and structural consequences.

Retrieving SNPs in TLRs pathway genes
Data on the human TLRs pathway genes were collected from national center for biological information (http://www.ncbi.nlm.nih.gov/) (accessed May 2015) ( Table 1)

SNP analysis
Mining the dbSNP-NCBI and UniProt databases revealed a total of 35802 SNPs in thirtyseven candidate genes in TLRs pathway ( Table 2).

SNPs & GO.
According to the PANTHER results, all 29 SNPs possessed the subPSEC score more than −3 and were therefore classified as deleterious ( Table   5). As shown in table 5, these SNPs were found to be as disease-associated with the probability >0.5 after analyzing by SNPs & GO.

Prediction of evolutionary conservation of amino acid position by ConSurf
Our ConSurf analysis revealed that all 29  (Table 6).

In silico solvent accessibility and threedimensional analyzes of native and mutant protein structures
By combining the results of SIFT, Poly-phen-2, PANTHER, SNPs & GO, I-Mutant 2.0, and ConSurf servers, 19 mutations were found to be more deleterious in candidate genes. Subsequently, these mutations were analyzed for solvent accessibility and stability, and the results were represented in the following paragraphs (see also      A: the wild-type residue (D) forms hydrogen bonds (green discontinuous line) with L155, V157, A158, L182 and S183; B: substitution of this amino acid with tyrosine will cause loss of hydrogen bonds with A158, L182 and S183. Moreover, the mutation showed a network of clashes (pink discontinuous line) with A158 and S183 residues.
hydrophobicity and charge. The difference in charge will disturb the ionic interactions of the wild type residue with D388, E389 and D398. R391H is annotated with rs55944915 in dbSNP database.
According to the PISA-database, the mutated residue is involved in a multimer contact. The new residue might be too small to make multimer contacts. In S151F variant, rs55824172 of TBK1 gene, the mutant residue (phenylalanine) is bigger and more hydrophobic than the wild-type (serine).
This conversion will cause the loss of hydrogen bonds in the core of the protein resulting in the disruption of correct folding.
We found that three SNPs in TLR1, including P733L (rs5743621), L697S (rs41311402) and L144P (rs117033348), were located in highly conserved regions and predicted to have functional and structural impacts on proteins. For P733L, the mutant residue (leucine) is bigger than the wildtype (proline) and is located on surface of the protein, potentially disturbing its interactions. For   (29). Moreover, it has been shown that rs696 G>A is associated with the susceptibility to different diseases including coronary artery disease and Behçet's disease (30)(31).
In conclusion, the current study reports the first pathway-based bioinformatics analysis of SNPs in TLRs pathway genes and provides a prioritized list of functional SNPs potentially affecting regulation and function of the pathway.
However, we noticed that the complexities of biological pathways merit the need for more experimentation to validate the true effect of these SNPs on TLRs network. Although the functional significance of the candidate SNPs was not experimentally assessed in this study, we believe that our results will help researchers interested in the roles of SNPs in TLRs pathways genes to focus on proper candidate variants.